Real-time Quality Inspection of Motor Rotor Using Cost-effective Intelligent Edge System

Zhu, Qingyun and Lu, Jingfeng and Wang, Xiaoxian and Wang, Hui and Lu, Siliang and de Silva, Clarence W. and Xia, Min (2023) Real-time Quality Inspection of Motor Rotor Using Cost-effective Intelligent Edge System. IEEE Internet of Things Journal, 10 (8). pp. 7393-7404. ISSN 2327-4662

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Abstract

Induction motors (IMs) are used extensively as driving actuators in electric vehicles. Motor rotors are prone to defects in the die casting procedure, which can significantly reduce the production quality. Benefitting from the development of Internet of things (IoT) techniques and edge computing, this study designed an instrumentation system for the fast inspection of rotor defects to meet the objectives of efficient and high-quality rotor production. First, an electromagnetic sensing device is designed to acquire the induced voltage signal of the rotor under investigation. Second, a residual multiscale feature fusion convolutional neural network model is designed to extract the hierarchical features of the signal, to facilitate defect recognition. The developed algorithm is deployed into a cost-effective edge computing node that includes a signal acquisition circuit and a Raspberry Pi microcontroller. The conducted experimental studies show that this implementation can achieve an inference time of less than 200 ms and accuracy of more than 99%. It is shown that the designed system exhibits superior performance when compared with conventional methods. The developed, compact and flexible handheld solution with enhanced deep learning techniques shows outstanding potential for use in real-time rotor defect detection.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Internet of Things Journal
Additional Information:
©2023 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1711
Subjects:
?? computer networks and communicationscomputer science applicationshardware and architectureinformation systemssignal processingsignal processinginformation systemsinformation systems and managementcomputer science applicationshardware and architecturecompu ??
ID Code:
184743
Deposited By:
Deposited On:
23 Jan 2023 13:45
Refereed?:
Yes
Published?:
Published
Last Modified:
12 Aug 2024 23:49